The Minimum Description Length Principle for Pattern Mining: A Survey

The aim of this document is to review the development of pattern mining methods based on and inspired from the Minimum Description Length (MDL) principle. Although this is an unrealistic goal, we strive for completeness. The reader is expected to be familiar with common pattern mining tasks and techniques, but not necessarily with concepts from information theory and coding, of which we therefore give an outline in Section 2. Background work is covered in Section 3, starting with the theory behind the MDL principle and similar principles, going over a few examples of uses of the principle in the adjacent fields of machine learning and natural language processing, and ending with a review of data mining methods that involve practical compression as a tool or that consider the problem of selecting patterns.